Original paper:Kojima S*, Koyama S, Ka M, Saito Y, Parrish EH, Endo M, Takata S, Mizukoshi M, Hikino K, Takeda A, Gelinas AF, Heaton SM, Koide R, Kamada AJ, Noguchi M, Hamada M, Biobank Japan Project Consor-tium, Kamatani Y, Murakawa Y, Ishigaki K, Nakamura Y, Ito K, Terao 8IMS researchers develop a novel algorithm that identifies and genotypes mobile genetic elements more accurately than ever before, enabling them to uncover newfound roles for these gene sequences in human diversity and disease.In 1983, DNA sequences that copy and insert them-selves throughout the genome – called mobile elements – made headlines when the American scientist Barbara Mc-Clintock won the Nobel Prize for their discovery. Decades of research later, mobile elements have been implicated in everything from the variegated color of corn kernels to the genetic transformation of normal cells into cancer cells. However, how they affect our susceptibility for disease re-mains to be resolved.To bridge this knowledge gap, Nicholas Parrish, Team Leader of the Genome Immunobiology RIKEN Hakubi Research Team at IMS, and his team set out to compre-hensively examine how mobile element variations (MEVs) contribute to differences in gene expression and disease risk. But first, the researchers needed a tool to extract mo-bile elements from genetic data.With current algorithms lacking sufficient accuracy and code availability, Shohei Kojima, Postdoctoral Researcher and first author of the study published in Nature Genet-ics, developed one from scratch. By inputting genetic data from a variety of local and global sources, Kojima devel-oped MEGAnE, a tool named after the Japanese word for glasses to highlight its ability to reveal mobile elements in fine detail.Indeed, MEGAnE discovered mobile element insertions and absences with a low false-positive rate of less than 6%, and genotyped mobile elements with over 90% accuracy. The algorithm is also highly efficient, which, Kojima noted, is crucial for analyzing the genomes of large cohorts.To glean insight into the similarities and differences in MEVs in humans across the globe, the team applied MEGAnE to genomic data from 2504 international par-ticipants in the 1000 Genomes Project. Unexpectedly, they discovered marked differences in the positions of a fam-ily of mobile elements called Alu between East Asian and non-East Asian populations.“To find that some human lineages have differences in the pattern in which mobile elements are mutating their genomes is really interesting,” commented Parrish. “It means East Asian populations are diversifying differently to non-East Asian populations.”Delving deeper to understand the mechanisms of MEVs, the team examined their impact on gene expression using data from 49 tissues catalogued in the Genotype-Tissue Expression project. Thanks to the statistical power of ME-GAnE, a whopping 1073 MEVs could be linked to gene ex-pression. This number leapfrogs the handful of associations identified in the majority of previous studies, Parrish noted.Finally, the team showed for the first time that MEVs can be integrated into genome-wide association studies to identify the specific genetic differences underlying the association of a gene to disease. In fact, using data from 180,000 individuals with 42 common diseases catalogued in BioBank Japan, the team linked five mobile element variations to three diseases.One of these associations was the insertion of mobile element LINE-1 within the NEDD4 gene with keloid skin lesions. Through cell culture experiments, the researchers confirmed that LINE-1 insertion enhances NEDD4 expres-sion, thereby increasing the risk of severe keloids – a find-ing that could open the door for more targeted drugs for patients.Going forward, the team plans to expand on their in-vestigations into the role of MEVs in population diversity to uncover the general patterns and mechanisms that make each of us unique.Figure: Uncovering the role of mobile elements in human health and diseaseDevelopment of an algorithm that accurately and effi-ciently identifies and genotypes mobile elements in hu-mans enabled mobile element variations (MEVs) to be ex-amined in multiple cohorts, including 180,000 individuals in BioBank Japan. Integration of MEV data into expression quantitative trait loci (eQTL) analysis revealed that MEVs impact gene expression in a variety of ways in different tissues. Further, a genome-wide association study (GWAS) integrating MEV data showed that insertion of LINE-1 in the NEDD4 gene increases the likelihood of severe keloid skin lesions, paving the way for the development of more targeted treatments.C, Momozawa Y, Parrish NF*. Mobile element variation contributes to population-specific genome diversification, gene regulation, and disease risk. Nat Genet 55, 939-951 (2023)Nicholas ParrishSeeing mobile elements under a new lens
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